Company Filing History:
Years Active: 2022-2024
Title: Innovations of Fengbin Chen
Introduction
Fengbin Chen is a notable inventor based in San Jose, CA, who has made significant contributions to the field of information retrieval and digital content management. With a total of 3 patents to his name, Chen's work focuses on enhancing the efficiency and effectiveness of digital media search and tagging systems.
Latest Patents
Chen's latest patents include "Retrieval Aware Embedding" and "Propagating Multi-Term Contextual Tags to Digital Content." The first patent describes systems and methods for information retrieval, where embodiments generate a dense embedding for each media object to be searched. It also involves generating a sparse embedding using an encoder that takes the dense embedding as input, ensuring that the sparse embedding meets a sparsity constraint during training. This innovative approach allows for more effective searches based on the sparse embedding. The second patent outlines systems and methods for determining multi-term contextual tags for digital content. It utilizes search query supervision to associate these tags with digital content and propagates them to additional content based on similarities, enhancing the search results based on the associated tags.
Career Highlights
Fengbin Chen is currently employed at Adobe, Inc., where he continues to develop cutting-edge technologies in the realm of digital content and information retrieval. His work at Adobe has positioned him as a key player in the advancement of innovative solutions that address the challenges of digital media management.
Collaborations
Chen has collaborated with notable colleagues, including Venkat Barakam and Benjamin Leviant, contributing to a dynamic and innovative work environment that fosters creativity and technological advancement.
Conclusion
Fengbin Chen's contributions to the field of information retrieval and digital content management are noteworthy. His innovative patents and work at Adobe, Inc. reflect his commitment to enhancing the efficiency of digital media systems.